Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
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Updated
Feb 11, 2025 - Python
Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
Solution to kaggle competition OTTO – Multi-Objective Recommender System: https://www.kaggle.com/competitions/otto-recommender-system
Scaling ML models with Taipy and Dask
A Dask native implementation of 'Term Frequency Inverse Document Frequency' for dask-ml and scikit-learn
one-stop destination for all machine learning and artificial intelligence library and algorithms
A Parallel segmentation algorithm of a flowers dataset using Dask.
Sentiment analysis on hotel reviews, using MongoDB, applying Dask parallel programming, comparing Recurrent and Convolutional neural networks and visualizating with Dash.
Word2vec for large corpus for Bangle
Preprocessing and predicting big data
BETA: Real-time inference from scalable machine learning in Python
In this repo, I build a LogisticRegression prediction model with Dask and PySpark and initialize an AWS EMR cluster to run the entire pipeline.
pybear is a Python computing library that augments data analytics functionality found in the popular numpy, scikit-learn, dask, and dask_ml libraries.
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